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HW 27 CLASS
Домашнее задание к уроку 27 в учебнике
Forecasting South Australian Energy Demand: Beating the Duck Curve
An end-to-end predictive analytics pipeline built in R using 30-minute interval data from AEMO. This project utilizes a Fourier-expanded ARIMA model to capture extreme intraday solar generation volatility. By modeling these daily cycles, the pipeline drops the baseline forecasting error (MAPE) from 35.8% down to 4.73%. Includes an embedded interactive Tableau dashboard tracking the 48-hour forward projections.
